Abstract
This paper presents a prediction method of fish movement based on learning its movement by using the Neural Network. The position of a fish is obtained by model-based matching and gazing-GA in real-time. The back-propagation is used for learning and predicting the movement of fish, where fish position is used as the input/teaching signal. The architecture and the internal parameter of the Neural Network are determined by basic experiments which use the simulated movement of fish. Experimental results using a swimming fish show that the proposed method can predict the movement of fish.
Original language | English |
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Pages | 2400-2405 |
Number of pages | 6 |
Publication status | Published - 2005 |
Externally published | Yes |
Event | SICE Annual Conference 2005 - Okayama, Japan Duration: Aug 8 2005 → Aug 10 2005 |
Other
Other | SICE Annual Conference 2005 |
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Country/Territory | Japan |
City | Okayama |
Period | 8/8/05 → 8/10/05 |
Keywords
- Back-propagation
- Gazing-GA
- Neural Network
- Visual Sarvoing
ASJC Scopus subject areas
- Control and Systems Engineering
- Computer Science Applications
- Electrical and Electronic Engineering